It is generally accepted that approximately one-quarter of North Americans have some degree of Coronary Artery Disease (CAD). It is also generally accepted that approximately half thereof are not reliably detectable by conventionally applied diagnostic techniques, such as noting contour changes in the S-T segments of electrocardiograms (ECG's). The problematic nature the situation poses is perhaps most critically apparent when one considers that perioperative complications can be much more prevalent and serious in a patient with (CAD) than in a normal patient who does not have (CAD). That is, knowledge that a patient has (CAD) can be critical in fostering morbidity and mortality reduction procedure planning and scheduling on the part of medical professionals. As well, detection of (CAD) is, of course, important in everyday matters such as the planning and execution of a simple exercise routine.
It is noted that conventional (ECG) analysis provides time domain graphical results based primarily upon the low frequency (e.g. 0 to 40 Hz), content of a subject's cardiac signals monitored by an (ECG) system. This is the case whether a Frank orthogonal X-Y-Z; a standard 12 Lead or a multi-Lead monitoring etc. (ECG) system is utilized. For instance, a Patent to Brown et al., U.S. Pat. No. 5,077,667 describes a method for measuring a clinically useful characteristic of a fibrillating heart related to the elapsed time since the onset of ventricular fibrillation. Their significant variable is the power in the frequency range of 7 to 8 Hz. The Brown et al. Patent describes the use of a transformation of sampled analog time domain signals into the frequency domain and subsequent analysis thereof as a step intermediate to applying corrective treatment to a fibrillating heart.
A U.S. Pat. No. 4,680,708 to Ambos et al., describes the use of a Fast Fourier Transform (FFT) applied to a portion of an (ECG) cycle. Mathematical analysis of the last forty (40) milliseconds of a waveform derived from the time domain (QRS) complex allows for calculation of a Figure Of Merit, (FOM), based upon the frequency content thereof. Said (FOM) is correlated to the likelihood of a patient experiencing ventricular tachycardia. While the Ambos et al. Patent mentions the presence of high frequency components in a signal derived from the (ECG), said Patent primarily focuses upon the analysis of frequencies between 20 and 50 Hertz in arriving at the (FOM). The Ambos et al. Patent further states that "Recent studies . . . have used a variety of low (25 to 100 Hz) and high (250 to 300 Hz) band pass filters. A major limitation . . . is a lack of a-priori knowledge of the frequency distribution of signals of interest and the inherent risk that filtering will exclude signals of particular interest."
Other recent investigation has focused upon the diagnostic capability inherent in the presence of particular high frequency components present in an (ECG) signal. For instance, a very recent paper by Aversano et al., titled "High Frequency QRS Electrocardiography In The Detection Of Reperfusion Following Thrombolytic Therapy", (see Clinical Cardiology, (17, 175-182, April 1994)), states that the amplitude of the high frequency components, (e.g. 150-250 Hz), of the (QRS) complexes decreases during cardiac ischemia, and returns to normal with resolution thereof. It is also stated that high frequency electrocardiography is a rapid and reliable bedside technique for discriminating between successful and failed reperfusion in patients treated with thrombolytic agents for myocardial infarction. The Aversano et al. paper also states that "Studies involving high-frequency QRS electrocardiography are few and modest."
A paper by Moss and Benhorin titled "Prognosis and Management After a First Myocardial Infarction", New England J. Medicine, Vol. 322, No. 11, 1990 points out the importance of being able to identify and distinguish patients with various types of (CAD) so that appropriate treatment can be prescribed. This paper, in conclusion acknowledges that noninvasive techniques currently available for detecting jeopardized ischemic myocardium are imperfect.
The above sampling of relevant prior reference materials shows that techniques such as direct morphologic analysis of conventional time domain signals, application of (FFT) to (ECG) time domain derived signals to provide frequency domain spectra for analysis, analysis of high frequency components of (ECG) signals and the focusing on specific portions of a QRS complex etc. are known. There remains, however, need for additional and more probative noninvasive methods of analyzing (ECG) derived data which allow incipient (CAD) in patients to be identified with improved certainty. In particular, there is a need for a method of accurately identifying subjects with (CAD), the validity of which has been shown to provide utility by actual clinical testing.
The present invention provides an improved method of analyzing (ECG) derived data which has been shown by actual test, (in view of an extensive data bank accumulated by the inventor containing both normal and abnormal (ECG) data), to enable greatly improved ability to accurately and noninvasively separate abnormal from normal cardiac subjects. The method of the present invention, for instance, routinely allows identification of subjects with truely silent (CAD), and subjects who do not present with the tell-tale nonspecific S-T and T wave changes. The method of the present invention also routinely allows identification of subjects with nonspecific S-T and T wave changes, and allows identification and separate classification of subjects with prior myocardial infarction, abnormal patients who present with normal (ECG), and simultaneously distinguishes the population of abnormal subjects who present with normal (ECG).